def test_cove_reader(n=10000):
plt.interactive(True)
try:
FIG = plt.figure()
Q = Queue()
bs_reader = BS3Reader(COVEProtocolHandler, Q, verbose=True,
ident='TestCOVE')
bs_reader.start()
for _ in xrange(n):
print Q.qsize()
try:
item = Q.get(block=True, timeout=2)
FIG.clf()
plt.imshow(item.data_lst[-1], shape=item.data_lst[-1].shape,
figure=FIG)
except Empty:
continue
except Exception, ex:
print ex
#
# Acknowledgements:
# Philipp Meier <*****@*****.**>
#_____________________________________________________________________________
#
##---IMPORTS
from numpy.testing import assert_equal, assert_almost_equal
import scipy as sp
from scipy.io import loadmat
from botmpy.common import TimeSeriesCovE, mcvec_from_conc, VERBOSE
from botmpy.nodes import BOTMNode
from spikeplot import plt
plt.interactive(False)
##---TESTS
def get_input_data(tf):
noise = loadmat('/home/phil/matlab.mat')['noise'].T
nc = noise.shape[1]
spike_proto_sc = sp.cos(sp.linspace(-sp.pi, 3 * sp.pi, tf))
spike_proto_sc *= sp.hanning(tf)
scale = sp.linspace(0, 2, tf)
cvals = [(5., .5), (4., 9.), (3., 3.), (7., 2.5)]
xi1 = sp.vstack([spike_proto_sc * cvals[i][0] * scale
for i in xrange(nc)]).T
xi2 = sp.vstack([spike_proto_sc * cvals[i][1] * scale[::-1]
for i in xrange(nc)]).T
temps = sp.asarray([xi1, xi2])
